Approaching Textual Entailment with LFG and FrameNet Frames
作者： Anette Frank , Aljoscha Burchardt
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摘要: We present a baseline system for modeling textual entailment that combines deep syntactic analysis with structured lexical meaning descriptions in the FrameNet paradigm. Textual is approximated by degrees of structural and semantic overlap text hypothesis, which we measure match graph. The encoded measures similarity are processed machine learning setting.1
参考文章(10)
Katrin Erk, Anette Frank, Aljoscha Burchardt, A WordNet Detour to FrameNet ,(2005)
Sebastian Padó, Katrin Erk, Shalmaneser - A Toolchain For Shallow Semantic Parsing language resources and evaluation. pp. 527- 532 ,(2006)
Ian Niles, Adam Pease, Linking Lixicons and Ontologies: Mapping WordNet to the Suggested Upper Merged Ontology. IKE. pp. 412- 416 ,(2003)
Dick Crouch, Packed Rewriting for Mapping Semantics to KR ,(2005)
Anette Frank, Katrin Erk, Towards an LFG Syntax-Semantics Interface for Frame Semantics Annotation conference on intelligent text processing and computational linguistics. pp. 1- 13 ,(2004) , 10.1007/978-3-540-24630-5_1
Mark A. Hall, Ian H. Witten, Eibe Frank, Data Mining: Practical Machine Learning Tools and Techniques ,(1999)
Collin F. Baker, Charles J. Fillmore, John B. Lowe, The Berkeley FrameNet Project meeting of the association for computational linguistics. ,vol. 1, pp. 86- 90 ,(1998) , 10.3115/980845.980860
Ted Pedersen, Satanjeev Banerjee, Extended gloss overlaps as a measure of semantic relatedness international joint conference on artificial intelligence. pp. 805- 810 ,(2003)
Stefan Riezler, Tracy H. King, Ronald M. Kaplan, Richard Crouch, John T. Maxwell, Mark Johnson, Parsing the wall street journal using a Lexical-Functional Grammar and discriminative estimation techniques Proceedings of the 40th Annual Meeting on Association for Computational Linguistics - ACL '02. pp. 271- 278 ,(2001) , 10.3115/1073083.1073129
B. Magnigni I Dagan, O. Glockman, None, The PASCAL Recognising Textual Entailment Challenge Lecture Notes in Computer Science. pp. 177- 190 ,(2006)